- Engineering Workflow Automation
- Design Space Exploration
Noesis Solutions’ engineering workflow automation enables engineering teams to set up and run simulation campaigns in a structured way, formalizing best practices into a well-documented and repeatable process. Rather than launching one particular instance of an engineering simulation workflow, development teams can use Design of Experiments to set up a sensibly planned series of experiments and get valuable insights into the design space.
But when dealing with resource intensive engineering simulations, sophisticated machine learning solutions are becoming increasingly important to speed up the entire process. Statistical learning techniques enable computers to learn, grow, change, and develop by themselves when exposed to new data. As machine learning can discover and display patterns buried in engineering simulation data, it has great potential to deliver highly accurate predictions in a short time and using a limited number of simulation experiments.